Vitamin D-related Genes and Metabolic Disorders

September 11, 2017 updated by: May Ahmad Baydoun, National Institute on Aging (NIA)

Vitamin D Receptor and Megalin Gene Polymorphisms and Their Association With Obesity, Central Obesity and the Metabolic Syndrome

The link between metabolic disturbances and vitamin D receptor (VDR) and MEGALIN (or LRP2) gene polymorphisms remains unclear, particularly among African-American adults. The associations of single nucleotide polymorphisms (SNPs) for VDR [rs1544410(BsmI:G/A), rs7975232(ApaI:A/C), rs731236(TaqI:G/A)] and MEGALIN [rs3755166:G/A,rs2075252:C/T, rs2228171:C/T] genes with incident and prevalent metabolic disturbances, including obesity, central obesity and metabolic syndrome (MetS) were evaluated.

From 1,024 African-Americans participating in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS, Baltimore, MD, 2004-2013) study, 539 subjects were selected who had complete genetic data as well as covariates selected for metabolic outcomes at two consecutive examinations (visits 1 and 2) with a mean follow-up time of 4.64±0.93y. Haplotype (HAP) analyses generated polymorphism groups that were linked to incident and prevalent metabolic disturbances.

Study Overview

Status

Completed

Conditions

Detailed Description

Adiposity, especially central adiposity, is a key component of the metabolic syndrome (MetS), which is accompanied by hyperglycemia, elevated blood pressure, lower HDL cholesterol and hypertriglyceridemia.(Ford, et al., 2003,Grundy, 1999)_ENREF_4 MetS increases the risk of type 2 diabetes (T2D) and cardiovascular disease by 1.7- and 5-folds, respectively.(Alberti, et al., 2009,Ford, et al., 2003,Galassi, et al., 2006) MetS is heritable and polygenic.(Maes, et al., 1997) Genetic variability contributes to 16%-85% of changes in Body Mass Index (BMI)(Yang, et al., 2007) and 37%-81% in waist circumference (WC) (e.g.(Ochs-Balcom, et al., 2011)). MetS is a major public health concern, increasing all-cause mortality rates, disability and health care costs.(Appels and Vandenbroucke, 2006,Bender, et al., 2006,Colditz, 1999,Doig, 2004,Ferrucci and Alley, 2007,Hill, et al., 2004,Solomon and Manson, 1997,Stevens, 2000,Wolf and Colditz, 1998) Obesity is implicated in the etiology of vitamin D deficiency. Serum 25-hydroxyvitamin D [25(OH)D] concentration correlates inversely with adiposity.(Beydoun, et al., 2010,Dorjgochoo, et al., 2012) Conversely, vitamin D3 may play a role in obesity by modulating intracellular calcium homeostasis, because higher intracellular calcium triggers lipogenesis and suppresses lipolysis.(Zemel, 2003) Many organs express vitamin D receptor (VDR), a part of the nuclear hormone receptor super-family. The VDR-1,25(OH)2D3 complex modulates transcription of vitamin D responsive genes(Kato, 2000) and influences adipocyte differentiation both in vitro and in vivo.(Wood, 2008) Epidemiological studies have shown associations of VDR gene polymorphisms with adiposity and related metabolic disorders.(Filus, et al., 2008,Grundberg, et al., 2004,Gu, et al., 2009,Ochs-Balcom, et al., 2011,Oh and Barrett-Connor, 2002,Ortlepp, et al., 2001,Ortlepp, et al., 2003,Speer, et al., 2001,Ye, et al., 2001) However, studies specifically examining adiposity outcomes either had small sample sizes (<400), (e.g.(Filus, et al., 2008,Grundberg, et al., 2004,Speer, et al., 2001)) or were restricted to one sex, (e.g. (Grundberg, et al., 2004,Ochs-Balcom, et al., 2011)) but more importantly were all cross-sectional or case-control by design.(Filus, et al., 2008,Grundberg, et al., 2004,Gu, et al., 2009,Ochs-Balcom, et al., 2011,Oh and Barrett-Connor, 2002,Ortlepp, et al., 2001,Ortlepp, et al., 2003,Speer, et al., 2001,Ye, et al., 2001) MEGALIN (aka low-density lipoprotein receptor-related protein-2 [LRP-2]), is the endocytic vitamin D-binding protein receptor which allows vitamin D entry into cells and whose expression is directly regulated by both vitamin D (Gressner, et al., 2008)) and vitamin A.(Liu, et al., 1998) MEGALIN may influences obesity by mediating leptin transport through the blood-brain barrier and modulating leptin signaling,(Dietrich, et al., 2008) or by facilitating transcytosis of its precursor hormone thyroglobulin.(Lisi, et al., 2005) Collectively, leptin and thyroid hormones affect adiposity through energy metabolism regulation.(Beydoun, et al., 2011) MEGALIN acting also as the receptor for sex-hormone binding globulin (SHBG) may play a role in the interaction between estrogen, vitamin D and intracellular calcium in adipocytes, resulting in sex-specific effects of MEGALIN polymorphisms on obesity phenotypes.(Ding, et al., 2008) In this study, it is hypothesized that selected polymorphisms in VDR and MEGALIN genes have sex-specific associations with several key metabolic disturbances in a longitudinal study of African-American urban adults.

Study Type

Observational

Enrollment (Actual)

1021

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

30 years to 64 years (Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Of the 3,720 baseline participants (mean±SD age(y) of 48.3±9.4, 45.3% men, and 59.1% African-American), genetic data were available on 1,024 African-American participants. Incomplete covariate data reduced the sample to n=769, while additional exclusions lead to a sample size ranging between 574 and 598 participants, with 539 having complete data on all baseline and follow-up outcome measures (cross-sectional part of the analysis). In the longitudinal analysis, metabolic disturbance-free at baseline participants were selected for each outcome. Sample sizes ranged from n=246 (central obesity-free) to n=466 (hyperglycemia-free). There were n=294 MetS-free individuals at baseline (Figure 1).

Description

Inclusion Criteria:

  1. 3,720 baseline participants (mean±SD age(y) of 48.3±9.4, 45.3% men, and 59.1% African-American),
  2. Genetic data were available on 1,024 African-American participants.
  3. Incomplete covariate data reduced the sample to n=769, while additional exclusions lead to a sample size ranging between 574 and 598 participants, with 539 having complete data on all baseline and follow-up outcome measures (cross-sectional part of the analysis).
  4. In the longitudinal analysis, metabolic disturbance-free at baseline participants were selected for each outcome. Sample sizes ranged from n=246 (central obesity-free) to n=466 (hyperglycemia-free).
  5. There were n=294 MetS-free individuals at baseline.

Exclusion Criteria:

  1. Whites in HANDLS, since they did not have any genetic data collected.
  2. All African-Americans in HANDLS without genetic data collected.
  3. All African-Americans in HANDLS with genetic data collected, who had incomplete data on key outcome variables and/or basic covariates of interest.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Obesity
Time Frame: 2004-2013
Obesity was defined as BMI≥30 kg/m2.
2004-2013
Central Obesity
Time Frame: 2004-2013
Central obesity was defined based on waist circumference (WC) ≥ 102 cm or 40 inches (men), ≥ 88 cm or 35 inches (women)
2004-2013
Metabolic Syndrome
Time Frame: 2004-2013
Participants who screened positive on at least 3 of 5 conditions ((1) central obesity (see above); (2) dyslipidemia: TAG≥1.695 mmol/L (150 mg/dl); (3) dyslipidemia: HDL-C<40 mg/dL (male), <50 mg/dL (female); (4) blood pressure≥130/85 mmHg; (5) fasting plasma glucose≥6.1 mmol/L (110 mg/dl).(39)) were classified as MetS-positive (2) Similarly, continuous annual rates of change (Δ) in metabolic outcomes were considered, specifically number of metabolic disturbances (MetD), BMI, WC, SBP, DBP, TAG, HDL-C, and Glucose. Binary incident outcomes included obesity, central obesity, MetS and other metabolic disturbance (i.e. hypertension, dyslipidemia-TAG, dyslipidemia-HDL and hyperglycemia).
2004-2013

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

National Institute on Aging (NIA)

Investigators

  • Principal Investigator: Alan B Zonderman, PhD, National Institute on Aging (NIA)
  • Principal Investigator: Michele K Evans, MD, National Institute on Aging (NIA)

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 18, 2004

Primary Completion (Actual)

July 7, 2013

Study Completion (Actual)

July 7, 2013

Study Registration Dates

First Submitted

September 8, 2017

First Submitted That Met QC Criteria

September 11, 2017

First Posted (Actual)

September 12, 2017

Study Record Updates

Last Update Posted (Actual)

September 12, 2017

Last Update Submitted That Met QC Criteria

September 11, 2017

Last Verified

September 1, 2017

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • NIA

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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